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To establish the predictive value of the QRESEARCH risk estimator version 3 (QRISK3) algorithm in identifying Spanish patients with ankylosing spondylitis (AS) at high risk of cardiovascular (CV) events and CV mortality. We also sought to determine whether to combine QRISK3 with another CV risk algorithm: the traditional SCORE, the modified SCORE (mSCORE) EULAR 2015/2016 or the SCORE2 may increase the identification of AS patients with high-risk CV disease. Information of 684 patients with AS from the Spanish prospective CARdiovascular in ReuMAtology (CARMA) project who at the time of the initial visit had no history of CV events and were followed in rheumatology outpatient clinics of tertiary centers for 7.5 years was reviewed. The risk chart algorithms were retrospectively tested using baseline data. After 4,907 years of follow-up, 33 AS patients had experienced CV events. Linearized rate=6.73 per 1000 person-years (95 % CI: 4.63, 9.44). The four CV risk scales were strongly correlated. QRISK3 correctly discriminated between people with lower and higher CV risk, although the percentage of accumulated events over 7.5 years was clearly lower than expected according to the risk established by QRISK3. Also, mSCORE EULAR 2015/2016 showed the same discrimination ability as SCORE, although the percentage of predicted events was clearly higher than the percentage of actual events. SCORE2 also had a strong discrimination capacity according to CV risk. Combining QRISK3 with any other scale improved the model. This was especially true for the combination of QRISK3 and SCORE2 which achieved the lowest AIC (406.70) and BIC (415.66), so this combination would be the best predictive model. In patients from the Spanish CARMA project, the four algorithms tested accurately discriminated those AS patients with higher CV risk and those with lower CV risk. Moreover, a model that includes QRISK3 and SCORE2 combined the best discrimination ability of QRISK3 with the best calibration of SCORE2. [Display omitted] [ABSTRACT FROM AUTHOR]

Nowadays there is a huge number of learning resources, covered different digital skills, on the Internet. In the framework of European Erasmus+ project: 'Digital Skills Accelerator' we developed dedicated to digital skills set of learning resources. Moreover, the test to analyses the level of user digital skills in form of the Online Self-Assessment Tool was developed as well. However, there is a problem with proper identification of personalized digital skills learning pathway. In the paper the expert system for creation of personalized digital skills learning pathway is proposed. The system runs on the DigComp framework to generate the user path, which consists of the ordered set of project learning resources from Digital Skills Accelerator. Selected resources best fit user's digital skills profile and will help in raising his/her digital competence. [ABSTRACT FROM AUTHOR]

Abstract Persistent Identifier (PID) systems have evolved in the last decade to mitigate the problem of link rot and provide unique and resolvable identifiers for digital objects, becoming a key element in archival services. However, they still depend on centralized services which may either become unavailable or cease to behave or be managed as expected. Decentralized technologies may serve as the infrastructure for the design of a trustless PID system over which other incentive mechanisms may be devised. Here we discuss a basic model for such a novel PID system, based on the capacity of content addressing of current decentralized file systems and the concept and definition of verifiable claims as metadata statements about the existence of an immutable digital resource. An example basic design is described using the Interplanetary File System (IPFS) as supporting infrastructure with a minimal set of conventions, that could be used as an alternate mechanism for storage of byte streams in digital repositories as DSpace or CKAN. [ABSTRACT FROM AUTHOR]

The increasing concern for the availability of scientific data has resulted in a number of initiatives promoting the archival and curation of datasets as a legitimate research outcome. Among them, dataset repositories fill the gap of providing long-term preservation of diverse kinds of data along with its meta-descriptions, and support citation. Unsurprisingly, the concern for quality arises as in the publication of papers. However, repositories support a larger variety of use cases, and many of them implement minimal control on the data uploaded by users. An approach to tackle with quality control in repositories is that of letting communities of users to filter the relevant resources for them, at the same time providing some form of trust to users of the data. However, there is a lack of knowledge of the extent to which this social approach that relies on communities self-organizing actually contributes to the effective organization inside repositories. This paper reports the results of a study on the Zenodo repository, describing its main contents and how communities have emerged naturally around the deposited contents. [ABSTRACT FROM AUTHOR]

Underwater EMR (UEMR) is an alternative procedure to conventional EMR (CEMR) to treat large, nonpedunculated colorectal lesions (LNPCLs). In this multicenter, randomized controlled clinical trial, we aimed to compare the efficacy and safety of UEMR versus CEMR on LNPCLs. We conducted a multicenter, randomized controlled clinical trial from February 2018 to February 2020 in 11 hospitals in Spain. A total of 298 patients (311 lesions) were randomized to the UEMR (n = 149) and CEMR (n = 162) groups. The main outcome was the lesion recurrence rate in at least 1 follow-up colonoscopy. Secondary outcomes included technical aspects, en bloc resection rate, R0 resection rates, and adverse events, among others. There were no differences in the overall recurrence rate (9.5% UEMR vs 11.7% CEMR; absolute risk difference, –2.2%; 95% CI, –9.4 to 4.9). However, considering polyp sizes between 20 and 30 mm, the recurrence rate was lower for UEMR (3.4% UEMR vs 13.1% CEMR; absolute risk difference, –9.7%; 95% CI, –19.4 to 0). The R0 resection showed the same tendency, with significant differences favoring UEMR only for polyps between 20 and 30 mm. Overall, UEMR was faster and easier to perform than CEMR. Importantly, the techniques were equally safe. UEMR is a valid alternative to CEMR for treating LNPCLs and could be considered the first option of treatment for lesions between 20 and 30 mm due to its higher en bloc and R0 resection rates. (Clinical trial registration number: NCT03567746.) [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: Journal impact factors continue to play an important role in research output assessment, in spite of the criticisms and debates around them. The impact factor rankings provided in the Journal Citation Reports (JCR™) database by Thompson Reuters have enjoyed a position of monopoly for many years. But this has recently changed with the availability of the Scopus™ database and its associated journal ranking published in the Scimago Journal Rank (SJR) Web page, as the former provides a citation database with similar inclusion criteria to those used in the JCR and the latter and openly accessible impact factor-based ranking. The availability of alternatives to the JCR impact factor listings using a different citation database raises the question of the extent to which the two rankings can be considered equally valid for research evaluation purposes. This paper reports the results of a contrast of both listings in Computer Science-related topics. It attempts to answer the validity question by comparing the impact factors of journals ranked in both listings and their relative position. The results show that impact factors for journals included in both rankings are strongly correlated, with SJR impact factors in general slightly higher, confirming previous studies related to other disciplines. Nonetheless, the consideration of tercile and quartile position of journal yields some divergences for journals appearing in both rankings that need to be accounted for in research evaluation procedures. [Copyright &y& Elsevier]

Abstract: The Ecological Metadata Language (EML) is an XML-based metadata specification developed for the description of datasets and their associated context in ecology. The conversion of EML metadata to an ontological form has been addressed in existing observation ontologies, which are able of providing a degree of computational semantics to the description of the datasets, including the reuse of scientific ontologies to express the observed entities and their characteristics. However, a number of practical issues regarding the automated translation of the available EML datasets to a representation with formal semantics and its subsequent integration into Research Information Systems (RIS) require separate attention. These issues include expressing meaning by using existing terminologies, the mapping of EML with models of research information and the mapping with mainstream metadata schema. This paper describes the approach taken for that purpose in the VOA3R project, describing the main mapping and translation decisions taken so far and some common pitfalls with metadata records as they are currently available through the Web. [Copyright &y& Elsevier]

Abstract: Collaborative filtering (CF) techniques have proved to be effective in their application to e-commerce and other application domains. However, their applicability to the recommendation of learning resources deserve separate attention as seeking learning resources can be hypothesized to be substantially different from selecting information resources or products for purchase. To date there are only a few scattered studies reporting on the application of well known user-based CF algorithms to learning object repositories. This paper reports an empirical study carried out by using MERLOT data and existing user-based CF algorithms. The aim of this preliminary study was that of finding evidence on accuracy measures of existing CF algorithms, and the relation of the items recommended with other elements of the repository. The results can be used as a starting point for future studies that account for the specific context of learning object repositories and the different aspects of preference in learning resource selection. [ABSTRACT FROM AUTHOR]

• Topic modelling and Social Network Analysis are used on online retrogaming forums. • Users' motivations to join retrogaming communities revolve around three main axes. • First, to socialize with like-minded people, sharing interests and experiences. • Second, to develop new games and projects for discontinued game systems. • Third, to participate in economic transactions and/or collecting. A noteworthy trend that has developed in video games in recent years is retrogaming. Retrogaming could be defined as a specific subculture of digital gaming typically characterised by playing (or collecting) obsolete personal computer, console or arcade video games in contemporary times, although it can also include playing modern games with "retro" aesthetics. However, it is not limited to that; it is also related to a wider cultural phenomenon that involves research, artistic activities, preservation and online discussions. This paper studies such activity in two separate sites, PlanetVB and AtariAge, aiming to uncover how the fan practices and the social networks that arise in these forums shape their communities, using natural language processing techniques combined with social network analysis. The results of the descriptive analysis on the language used in online forums show how most users participate in such online sites to buy and sell collectibles, to program new games for old systems or to simply socialise with like-minded people, collectively bringing new life into discontinued game systems. [ABSTRACT FROM AUTHOR]

Patients with coronavirus disaese 2019 (COVID-19) can develop a cytokine release syndrome that eventually leads to acute respiratory distress syndrome requiring invasive mechanical ventilation (IMV). Because IL-6 is a relevant cytokine in acute respiratory distress syndrome, the blockade of its receptor with tocilizumab (TCZ) could reduce mortality and/or morbidity in severe COVID-19. We sought to determine whether baseline IL-6 serum levels can predict the need for IMV and the response to TCZ. A retrospective observational study was performed in hospitalized patients diagnosed with COVID-19. Clinical information and laboratory findings, including IL-6 levels, were collected approximately 3 and 9 days after admission to be matched with preadministration and postadministration of TCZ. Multivariable logistic and linear regressions and survival analysis were performed depending on outcomes: need for IMV, evolution of arterial oxygen tension/fraction of inspired oxygen ratio, or mortality. One hundred forty-six patients were studied, predominantly males (66%); median age was 63 years. Forty-four patients (30%) required IMV, and 58 patients (40%) received treatment with TCZ. IL-6 levels greater than 30 pg/mL was the best predictor for IMV (odds ratio, 7.1; P <.001). Early administration of TCZ was associated with improvement in oxygenation (arterial oxygen tension/fraction of inspired oxygen ratio) in patients with high IL-6 (P =.048). Patients with high IL-6 not treated with TCZ showed high mortality (hazard ratio, 4.6; P =.003), as well as those with low IL-6 treated with TCZ (hazard ratio, 3.6; P =.016). No relevant serious adverse events were observed in TCZ-treated patients. Baseline IL-6 greater than 30 pg/mL predicts IMV requirement in patients with COVID-19 and contributes to establish an adequate indication for TCZ administration. [ABSTRACT FROM AUTHOR]